code: def __init__(
      self,
      input1_size,
      input2_size,
      hidden_size,
      output_size,
      hidden_func=F.relu,
      dropout=0,
      pairwise=True,
  ):
      super().__init__()
      self.W1 = nn.Linear(input1_size, hidden_size)
      self.W2 = nn.Linear(input2_size, hidden_size)
      self.hidden_func = hidden_func
      if pairwise:
          self.scorer = PairwiseBiaffineScorer(
              hidden_size, hidden_size, output_size
          )
      else:
          self.scorer = BiaffineScorer(
              hidden_size, hidden_size, output_size
          )
      self.dropout = nn.Dropout(dropout)
  
file_path: stanza/stanza/models/common/biaffine.py
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new DeepBiaffineScorer object from inherited base classes: nn with example: obj = DeepBiaffineScorer(input1_size, input2_size, hidden_size, output_size, hidden_func, dropout, pairwise)